From Amoeba to Cognition Frankfurt Institute of Advanced Studies

April 16, 2003

Christoph von der Malsburg Institut für Neuroinformatik

und Fakultät für Physik und AstronomieRuhr-University Bochum, Germany

andComputer Science Departmentand Program in Neuroscience

University of Southern CaliforniaLos Angeles

Amoeba

Euglena

Repertoire of single-celled animals 1

Metabolism

• Production, transformation and breakdown of molecules

• Synthesis of molecules under genetic control

• Regulation, e.g., of ionic concentrations

• Transport of molecules, inside, in and out of cell

• Electrical “behavior”

• Circadian rhythm

Reproduction

Repertoire of single-celled animals 2

Behavior

•Sensing (light, sound, chemical milieu)

•Self-shaping (pseudopodia, mitosis)

•Motility, esp. chemotaxis

•Feeding: ingestion and digestion

•Aggression, flight

•Signalling

•Collaboration (e.g., slime mold, biofilms)

Amoeba aggregation 2

Spiral waves

Ants

Neuron 1

Neuron 2

Synapse

The Ontogenetic “Riddle”

• Information content of the genome: 109 bits

• Information content of the brain’s wiring: 1016 bits

(1010 neurons, hence ld 1010 = 33 bits per connection,

times 1015 synapses = 1016 bits of information)

• Solution: genetically controlled self-organization

Rettec anatomical schemaA Model for the Ontogenesis of Retinotopy

(Willshaw and Malsburg, 1976)

Rettec functional schma

• Chemotaxis

• Synaptic plasticity controlled by electrical signals

Hebbian Plasticity

Correlation-controlled Synaptic Plasticity

(“Hebbian Plasticity”)

Time10 sec

Meister

(Prenatal ferret retina, M. Meister et al.)

Network Self-Organization

Network Signals

Signal Dynamic

Synaptic Plasticity

Rettec functional schma

Rettec principle 2

Rettec development

Visual system schema

Levay stripes

Binoc 1 A Model for the Ontogenesis of Ocularity Domains (Biol. Cybernetics, 1977)

Binoc 2

H&W orient

Devalois 2

73 projectionA model for the development of orientation-

specific neurons (Kybernetik, 1973)

Retina

Cortex

Connection Strength

73 stimuli Retinal Stimuli

Meister

(Prenatal ferret retina, M. Meister et al.)

73 cell 70 Re-organization of a cortical receptive field

73 cortex post

73 orientmap

Devalois 1

Gabors

Olshausen-and Field: Schema

Development of connections strengths Φi(x,y) under 2 constraints:

• Preservation of information (ability to reconstruct)

• Sparsity

Natural images

Olshausen-Field Gabors

Points of Conclusion:

• Retinotopy, orientation specificity as paradigmsof network self-organization and CNS ontogenesis

• Ontogenesis of CNS and cellular repertoire

• Amount of genetic information

Invariant object Recognition(As paradigm of a cognitive function)

image model

van Essen

Rubfig 1Image Domain Model Domain

Model Window

Object recognition

Rubfig 2Image Domain Model Domain

Model Window

Objection recognition 2

Temporal binding

Temporal binding

Rapid, Reversible Synaptic Plasticity

Time10 msec

Network Self-Organization

Network Signals

Signal Dynamic

Synaptic Plasticity

Image-to-jets

Maryl-representation

2D mapping formation

Face recognition rates

Model Probe Size Recognition rate *

Other systems

frontal Diff expressionlarge transform

124 85%

frontal Diff expressionsmall transform

124 96.8% 98% (=245/250)(Wiskott et al 97)

frontal 30° rotation in depth

110 93.6% 66.4% (=73/110)(Wiskott & Malsburg 96)

* After 3 iterations

Points of Conclusion:

• Evolution as a game of varying the eurkaryote’s repertoire

• Ontogenesis as a refinement of old cellular behavioral patterns

• reproduction, differentiation

• cellular migration, chemotaxis

• chemical signalling, reaction-diffusion patterns

• putting out of “pseudopodia”

• Brain function as a fast version of the same game again

• Network Self-Organization the central process

Outlook

• The flexibility of the human brain shows that fundamental principles are at work

• Similar conclusions may be drawn from the rapid development of human society

• Elucidating the general principles of organization is the challenge of our times

• This issue has at present no academic home

Molecular Biology

The Software Crisis

NIST Study 02: yearly US loss due to SW failure: $60 Billion

Human:

Detailed Communication

Machine:

Creative Infrastructure: Goals, Methods, Interpretation, World Knowledge, Diagnostics

Algorithms: deterministic, fast, clue-less

Algorithmic Division of LaborAlgorithmic

DOL

Human:

Loose Communication

Machine:

Goal Definition

Creative Infrastructure:Goals, Methods, Interpretation, World Knowldege, Debugging

Data, „Algorithms“

Organic ComputersOrganic

Computers

Self-Organization in Need of Development

The ideas of self-organization have created a revolution, but they are now in need of forceful further development!

Underdeveloped aspects:

• Control of the control parameters (Ashby’s super-stability)

• Explicit representation of goals

• Cascades of organization (description of unfolding systems)

• Escaping geometry (e.g., network self-organization)

Physics to the Rescue!!• Physics has a proven track-record of understanding complex

phenomena on the basis of simple paradigms and principles

• Physics is in possession of highly relevant methodology(statistical mechanics, systems of non-linear differential equations)

• Physics has a very successful system of education

• Physics is on the look-out for a new application field